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G-DNA (GPU-based DNA aligner)
is the first highly parallel solution
that has been optimized to process nucleotide
reads (DNA/RNA) from modern sequencing machines.
Results show that the software is very efficient
on both multi-GPU machines and MPI+GPU clusters.
It computes scores and shifts for a given set of
sequence pairs. It might be used as an efficient
aligning tool in de-novo assembly.

G-MSA -- a valuable
tool for the MSA problem which is efficient and can be
run on a common personal computer equipped with
NVIDIA GPU (G80, GT200 or Fermi).
Extensive tests show its
great speedup in comparison to
the T-Coffee method on which it was based
whereas the quality of the results remained
very high.
Moreover, multi-GPU support influences
the execution time considerably.

gpu-pairAlign (G-PAS) implements global and semiglobal
Needleman-Wunsch, and Smith-Waterman algorithms with
a backtracking
procedure which is needed to construct the alignment.
Our solution performs the alignment of every given
sequence pair, which is a
required step e.g. for progressive
multiple sequence alignment methods, as well as
for DNA recognition at the DNA assembly stage.
Tests show that the
implementation, with performance up to 6.3 GCUPS
on a single GPU for affine gap penalties,
is very efficient in comparison to other
CPU and GPU-based solutions.
Moreover, multiple GPUs support with load balancing
makes the application very scalable.

G-MAPSEQ is a tool for mapping Next Generation Sequencing reads to the reference genome. The solution connects two basic ideas - fast heuristic to determine candidates for similar pairs of sequences (where one is the read, and the second is a fragment of reference sequence) and exact, ultrafast semiglobal pairwise alignment method which is performed on GPU, to check if the candidates are real mapping positions. G-MAPSEQ supports both: single and pairend reads.